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generative-ai-python API reference

65 public APIs from generative-ai-python (google/generative-ai-python) — 38 classes, 12 functions, 15 methods. Signatures extracted by static analysis of the actual source.

Repository: google/generative-ai-python

KindCount
Classes38
Functions12
Methods15

API list

classgoogle.generativeai.caching.CachedContent
Cached content resource.
methodgoogle.generativeai.caching.CachedContent.delete() -> None
Deletes `CachedContent` resource.
methodgoogle.generativeai.caching.CachedContent.get(name:str) -> CachedContent
Fetches required `CachedContent` resource.
methodgoogle.generativeai.caching.CachedContent.list(page_size:Optional[int]=1) -> Iterable[CachedContent]
Lists `CachedContent` objects associated with the project.
classgoogle.generativeai.generative_models.ChatSession
Contains an ongoing conversation with the model.
methodgoogle.generativeai.generative_models.ChatSession.history() -> list[protos.Content]
The chat history.
classgoogle.generativeai.notebook.argument_parser.ArgumentParser
Customized ArgumentParser for LLM Magics.
classgoogle.generativeai.notebook.argument_parser.ParserError
Exception thrown when there is an error.
classgoogle.generativeai.notebook.argument_parser.ParserNormalExit
Exception thrown when the parser exits normally.
classgoogle.generativeai.notebook.cmd_line_parser.CmdLineParser
Implementation of Magics command line parser.
classgoogle.generativeai.notebook.compare_cmd.CompareCommand
Implementation of "compare" command.
classgoogle.generativeai.notebook.compile_cmd.CompileCommand
Implementation of the "compile" command.
classgoogle.generativeai.notebook.eval_cmd.EvalCommand
Implementation of "eval" command.
classgoogle.generativeai.notebook.flag_def.BooleanFlagDef
Definition for a Boolean flag.
classgoogle.generativeai.notebook.flag_def.FlagDef
Abstract base class for flag definitions.
methodgoogle.generativeai.notebook.flag_def.FlagDef.add_argument_to_parser(parser:argparse.ArgumentParser) -> None
Adds this flag as an argument to `parser`.
classgoogle.generativeai.notebook.flag_def.MultiValuesFlagDef
Definition for a flag that takes multiple values.
classgoogle.generativeai.notebook.flag_def.SingleValueFlagDef
Definition for a flag that takes a single value.
classgoogle.generativeai.notebook.gspread_client.GSpreadClient
Wrapper around gspread.client.Client.
classgoogle.generativeai.notebook.gspread_client.GSpreadClientImpl
Concrete implementation of GSpreadClient.
classgoogle.generativeai.notebook.gspread_client.NullGSpreadClient
Null-object implementation of GSpreadClient.
funcgoogle.generativeai.notebook.gspread_client.authorize(creds:credentials.Credentials, env:ipython_env.IPythonEnv | None) -> None
Sets up credential for gspreads.
funcgoogle.generativeai.notebook.gspread_client.testonly_set_client(client:GSpreadClient) -> None
Overrides the global client for testing.
funcgoogle.generativeai.notebook.html_utils.get_anchor_tag(url:sheets_id.SheetsURL, text:str) -> str
Returns a HTML string representing an anchor tag.
classgoogle.generativeai.notebook.ipython_env_impl.IPythonEnvImpl
Concrete implementation of IPythonEnv.
classgoogle.generativeai.notebook.lib.llm_function.LLMCompareFunction
LLMFunction for comparisons.
classgoogle.generativeai.notebook.lib.llmfn_output_row.LLMFnOutputRowView
Immutable view of LLMFnOutputRow.
methodgoogle.generativeai.notebook.lib.llmfn_output_row.LLMFnOutputRowView.result_key() -> str
Get the key of the result cell.
methodgoogle.generativeai.notebook.lib.llmfn_output_row.LLMFnOutputRowView.result_value() -> Any
Get the value of the result cell.
classgoogle.generativeai.notebook.lib.llmfn_outputs.LLMFnOutputs
A sequence of LLMFnOutputEntry instances.
methodgoogle.generativeai.notebook.lib.llmfn_outputs.LLMFnOutputs.export(sink:LLMFnOutputsSink) -> None
Export contents to `sink`.
classgoogle.generativeai.notebook.lib.llmfn_outputs.LLMFnOutputsBase
Parent class for LLMFnOutputs.
methodgoogle.generativeai.notebook.lib.llmfn_outputs.LLMFnOutputsBase.as_dict() -> Mapping[str, Sequence[Any]]
Formats returned results as dictionary.
classgoogle.generativeai.notebook.lib.model.EchoModel
Model that returns the original input.
classgoogle.generativeai.notebook.lib.model.ModelArguments
Common arguments for models.
classgoogle.generativeai.notebook.lib.model.ModelResults
Results from calling AbstractModel.call_model().
funcgoogle.generativeai.notebook.lib.prompt_utils.get_placeholders(prompt:str) -> AbstractSet[str]
Returns the placeholders for `prompt`.
classgoogle.generativeai.notebook.magics.AbstractMagics
Defines interface to Magics class.
classgoogle.generativeai.notebook.magics.Magics
Class to register the magic with Colab.
methodgoogle.generativeai.notebook.magics.Magics.get_instance() -> AbstractMagics
Retrieve global instance of the Magics object.
classgoogle.generativeai.notebook.magics.MagicsImpl
Actual class implementing the magics functionality.
funcgoogle.generativeai.notebook.magics.authorize(creds:credentials.Credentials) -> None
Sets up credentials.
classgoogle.generativeai.notebook.magics_engine.MagicsEngine
Implementation of functionality used by Magics.
classgoogle.generativeai.notebook.model_registry.ModelRegistry
Registry that instantiates and caches models.
funcgoogle.generativeai.notebook.output_utils.write_to_outputs(results:llmfn_outputs.LLMFnOutputs, parsed_args:parsed_args_lib.ParsedArgs) -> None
Writes `results` to the sinks provided.
classgoogle.generativeai.notebook.parsed_args_lib.ParsedArgs
The results of parsing the command line.
classgoogle.generativeai.notebook.post_process_utils.PostProcessParseError
An error parsing the post-processing tokens.
funcgoogle.generativeai.notebook.py_utils.get_py_var(var_name:str) -> Any
Retrieves the value of `var_name` from the global environment.
funcgoogle.generativeai.notebook.py_utils.set_py_var(var_name:str, val:Any) -> None
Sets the value of `var_name` in the global environment.
funcgoogle.generativeai.notebook.py_utils.validate_var_name(var_name:str) -> None
Validates that the variable name is a valid identifier.
classgoogle.generativeai.notebook.run_cmd.RunCommand
Implementation of the "run" command.
funcgoogle.generativeai.notebook.sheets_sanitize_url.sanitize_sheets_url(url:str) -> str
Sanitize a Sheets URL.
classgoogle.generativeai.notebook.sheets_utils.SheetsInputs
Inputs to an LLMFunction from Google Sheets.
funcgoogle.generativeai.operations.get_operation(name:str, *client=None) -> CreateTunedModelOperation
Calls the API to get a specific operation
funcgoogle.generativeai.operations.list_operations(*client=None) -> Iterator[CreateTunedModelOperation]
Calls the API to list all operations
classgoogle.generativeai.types.model_types.Model
A dataclass representation of a `protos.Model`.
classgoogle.generativeai.types.model_types.TunedModel
A dataclass representation of a `protos.TunedModel`.
classgoogle.generativeai.types.permission_types.Permission
A permission to access a resource.
methodgoogle.generativeai.types.permission_types.Permission.delete(client:glm.PermissionServiceClient | None=None) -> None
Delete permission (self).
methodgoogle.generativeai.types.permission_types.Permission.get(name:str, client:glm.PermissionServiceClient | None=None) -> Permission
Get information about a specific permission.
methodgoogle.generativeai.types.permission_types.Permissions.get(name:str) -> Permission
Get information about a specific permission.
methodgoogle.generativeai.types.permission_types.Permissions.get_async(name:str) -> Permission
Get information about a specific permission.
classgoogle.generativeai.types.retriever_types.Corpus
A `Corpus` is a collection of `Documents`.
classgoogle.generativeai.types.retriever_types.Document
A `Document` is a collection of `Chunk`s.
methodgoogle.generativeai.types.retriever_types.Document.list_chunks(page_size:int | None=None, client:glm.RetrieverServiceClient | None=None, request_options:helper_types.RequestOptionsType | None=None) -> Iterable[Chunk]
List chunks of a document.

About this data

These signatures were extracted from the public source of google/generative-ai-python using Python's ast module. Argument names, default values, type annotations and return types are taken verbatim from the code. Implementation bodies are never stored. See how it works for details.

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